Machine vision techniques, such as simultaneous localization and mapping (SLAM), augmented reality (AR), and virtual reality (VR), often rely on the identification of objects within the local environment of a device through the analysis of imagery of the local environment captured by the device. Such objects typically are represented as collections of two-dimensional (2D) feature descriptors, which reflect the orientation and distance of the imaging camera from the object when the corresponding image was taken. When comparing different images related to the object to, for example, verify that the same object is represented in both images, the 2D feature descriptors in each image typically are compared to determine a match. This 2D feature descriptor comparison process is impacted by the fact that the sets of 2D feature descriptors being compared may have been obtained from different observation directions or distances.